Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Franceschelli, Giorgio"'
The training process of foundation models as for other classes of deep learning systems is based on minimizing the reconstruction error over a training set. For this reason, they are susceptible to the memorization and subsequent reproduction of trai
Externí odkaz:
http://arxiv.org/abs/2407.13493
Large language models are revolutionizing several areas, including artificial creativity. However, the process of generation in machines profoundly diverges from that observed in humans. In particular, machine generation is characterized by a lack of
Externí odkaz:
http://arxiv.org/abs/2405.00099
The Overfitted Brain hypothesis suggests dreams happen to allow generalization in the human brain. Here, we ask if the same is true for reinforcement learning agents as well. Given limited experience in a real environment, we use imagination-based re
Externí odkaz:
http://arxiv.org/abs/2403.07979
Publikováno v:
JAIR 79 (2024) 417-446
Generative Artificial Intelligence (AI) is one of the most exciting developments in Computer Science of the last decade. At the same time, Reinforcement Learning (RL) has emerged as a very successful paradigm for a variety of machine learning tasks.
Externí odkaz:
http://arxiv.org/abs/2308.00031
Large Language Models (LLMs) are revolutionizing several areas of Artificial Intelligence. One of the most remarkable applications is creative writing, e.g., poetry or storytelling: the generated outputs are often of astonishing quality. However, a n
Externí odkaz:
http://arxiv.org/abs/2304.00008
Autor:
Franceschelli, Giorgio1 (AUTHOR) giorgio.franceschelli@unibo.it, Musolesi, Mirco2 (AUTHOR) m.musolesi@ucl.ac.uk
Publikováno v:
ACM Computing Surveys. Nov2024, Vol. 56 Issue 11, p1-41. 41p.
Publikováno v:
Intelligenza Artificiale 16, 2 (2022), 151-163
Measuring machine creativity is one of the most fascinating challenges in Artificial Intelligence. This paper explores the possibility of using generative learning techniques for automatic assessment of creativity. The proposed solution does not invo
Externí odkaz:
http://arxiv.org/abs/2201.06118
Publikováno v:
Data & Policy. 2022;4:e17
Machine-generated artworks are now part of the contemporary art scene: they are attracting significant investments and they are presented in exhibitions together with those created by human artists. These artworks are mainly based on generative deep
Externí odkaz:
http://arxiv.org/abs/2105.09266
There is a growing interest in the area of machine learning and creativity. This survey presents an overview of the history and the state of the art of computational creativity theories, key machine learning techniques (including generative deep lear
Externí odkaz:
http://arxiv.org/abs/2104.02726
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